Frontiers in psychology · 2026
Smartphones in the classroom: power tool or source of distraction? Evidence from a cross-lagged panel study.
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Li Xiaogang, Chen Liping
Аннотация
BACKGROUND: The widespread use of mobile devices in educational settings suggests that smartphones may function both as learning tools and as potential sources of distraction. Existing cross-sectional studies have been unable to adequately explain the dynamic causal relationships among technology acceptance, digital distraction, and academic engagement.
OBJECTIVE: This study aims to examine the reciprocal relationships among these three variables using a longitudinal design, thereby providing empirical evidence for the integration of educational technology.
METHODS: A three-wave longitudinal survey (conducted at six-month intervals) was administered to an initial sample of 1,200 high school students from three public secondary schools in eastern China; 1,020 participants (retention rate: 85.0%) were retained through all three waves and included in the final analysis (attrition confirmed as non-systematic via Little's MCAR test, p = 0.78). Data were collected using validated scales assessing technology acceptance, classroom digital distraction, and academic engagement. Cross-lagged panel models (CLPM) and bootstrap mediation analysis (5,000 resamples) were employed to examine reciprocal longitudinal relationships and indirect effects among the variables.
RESULTS: (1) Technology acceptance positively predicted subsequent digital distraction (β = 0.12-0.14, p < 0.01) but had no significant direct effect on academic engagement. (2) Digital distraction negatively predicted subsequent academic engagement (β = -0.23--0.25, p < 0.001). (3) Academic engagement negatively predicted subsequent digital distraction (β = -0.08 to -0.09, p < 0.05) and positively predicted subsequent technology acceptance (β = 0.18 to 0.20, p < 0.001). (4) Digital distraction fully mediated the relationship between technology acceptance and academic engagement (indirect effect = -0.032, 95% CI = [-0.059, -0.013]).
CONCLUSION: The role of mobile phones in education is neither a fixed "power tool" nor an inevitable "distractor," but rather depends on the dynamic interaction among technological perceptions, behavioral regulation, and learning contexts. The educational value of technology adoption should undergo a transformative process of "assessment," in which digital distraction serves as a critical gatekeeper. Educational practice should transcend the binary dilemma of "prohibition" versus "overuse" and focus on cultivating students' self-regulation skills and critical literacy in technology use, thereby advancing an educational philosophy of "teaching according to individual aptitude" in the digital age.
OBJECTIVE: This study aims to examine the reciprocal relationships among these three variables using a longitudinal design, thereby providing empirical evidence for the integration of educational technology.
METHODS: A three-wave longitudinal survey (conducted at six-month intervals) was administered to an initial sample of 1,200 high school students from three public secondary schools in eastern China; 1,020 participants (retention rate: 85.0%) were retained through all three waves and included in the final analysis (attrition confirmed as non-systematic via Little's MCAR test, p = 0.78). Data were collected using validated scales assessing technology acceptance, classroom digital distraction, and academic engagement. Cross-lagged panel models (CLPM) and bootstrap mediation analysis (5,000 resamples) were employed to examine reciprocal longitudinal relationships and indirect effects among the variables.
RESULTS: (1) Technology acceptance positively predicted subsequent digital distraction (β = 0.12-0.14, p < 0.01) but had no significant direct effect on academic engagement. (2) Digital distraction negatively predicted subsequent academic engagement (β = -0.23--0.25, p < 0.001). (3) Academic engagement negatively predicted subsequent digital distraction (β = -0.08 to -0.09, p < 0.05) and positively predicted subsequent technology acceptance (β = 0.18 to 0.20, p < 0.001). (4) Digital distraction fully mediated the relationship between technology acceptance and academic engagement (indirect effect = -0.032, 95% CI = [-0.059, -0.013]).
CONCLUSION: The role of mobile phones in education is neither a fixed "power tool" nor an inevitable "distractor," but rather depends on the dynamic interaction among technological perceptions, behavioral regulation, and learning contexts. The educational value of technology adoption should undergo a transformative process of "assessment," in which digital distraction serves as a critical gatekeeper. Educational practice should transcend the binary dilemma of "prohibition" versus "overuse" and focus on cultivating students' self-regulation skills and critical literacy in technology use, thereby advancing an educational philosophy of "teaching according to individual aptitude" in the digital age.